Paper ID #9715Embedding Systems Engineering Practices into Systems Engineering ClassesDr. S. Gary Teng, University of North Carolina, Charlotte Dr. S. Gary Teng is Professor of Systems Engineering & Engineering Management and Director of Center for Lean Logistics and Engineered Systems at the University of North Carolina at Charlotte. He holds a P.E. license in the State of Wisconsin and is an ASQ-certified Quality Engineer and Reliability Engineer. His research interests are in engineering system design, analysis and management, supply chain management, lean systems, and risk management. Dr. Teng received the Bernard R
view of value, trade-offs, and optimization;3. Understanding system’s interactions and states (modes);4. Specifying system technical requirements;5. Creating and analyzing high level design;6. Assessing solution feasibility, consistency, and completeness;7. Performing system failure mode and risk analysis;8. Planning system families, platforms, and product lines;9. Understanding roles and interdependencies across the innovation process.Within the summer grand challenge program only a subset of these system competencies havebeen introduced.The framework for the system’s competencies aspect of the course included utilization of asystems engineering approach as described by the S*-metamodel (shown in Figure 1)[4]. Themodel based systems
Smith (2013). The mean andstandard deviation of the ratings were reported and observations were made. In general,students gave higher ratings on encouraging the future use of Piazza than Praze and Panopto.Students also thought Piazza was easier to use than Praze and Praze was easier to use thanPanopto. When asked to compare SYS 2001 to other courses, students agreed the most withthe statement that ―Compared to other courses, this course used technology to allow moreface-to-face interaction with the instructor(s) and other students.‖ 97% students agreed orstrongly agreed that they received more feedback in SYS 2001 than other courses and 67%agreed or strongly agreed that the structure of the course and the technologies used helpedstudents
the IEEE Std 830-1998 Recommended Practice for SoftwareRequirements Specifications.” In addition, the students’ submissions should also address thefollowing tasks: • Identify the section(s) of your Requirements Document where the information related to the requirements’ customers and stakeholders is to be presented. Provide the customers and stakeholders information as part of the document or as an Appendix. • Identify the section(s) of your Requirements Document where, besides the natural language requirements, the requirements analysis and specification process would benefit from the use of diagrams (use cases, data flow diagrams, state-machine-diagrams, etc.) to better understand the needed
risk analysis for over twenty five years. He served for two and a half years as a research mathematician at the international operations and process research laboratory of the Royal Dutch Shell Company. While at Shell, Dr. Mazzuchi was involved with reliability and risk analysis of large processing systems, maintenance optimization of off-shore platforms, and quality control procedures at large scale chemical plants. During his academic career, he has held research contracts in development of testing procedures for both the U.S. Air Force and the U.S. Army, in spares provisioning modeling with the U. S. Postal Service, in mission assurance with NASA, and in maritime safety and risk assessment with the Port Authority
the top lessons learned by the Dual-Use Ferry student teams. Atthe end of the design effort, a design solution was provided to the customer. The customer wasvery pleased with the resulting effort and stated that future marketplace design efforts would bewelcomed and supported.AcknowledgmentsWe thank the Department of Defense for financial support of the capstone marketplace projectand for technical and logistical support in providing mentors and sponsors. We thank the mentorsand sponsors of the Dual-Use Ferry project for their generous support and guidance. Finally, wethank the students at Stevens Institute and UAH for their hard work on this challenging project.Bibliography 1. B. McGrath, S. Lowes, A. Squires and C. Jurado, SE Capstone
discussion and advice regarding PBL implementation; George Chiu for support ofthe work at Purdue; and the reviewers for thoughtful comments which improved the work.References 1. Smith, K., Sheppard, S., Johnson, D., and Johnson, R. (2005) “Pedagogies of Engagement: Classroom- Based Practices.” Journal of Engineering Education, Vol. 94, No. 1, pp. 87-101. 2. Smith, K. (2011) “Cooperative Learning: Lessons and Insights from Thirty Years of Championing a Research-Based Innovative Practice.” Proceedings of the 41st ASEE/IEEE Frontiers in Education Conference, Rapid City, SD. 3. Prince, M. (2004) “Does Active Learning Work? A Review of the Research.” Journal of Engineering Education, Vol. 93, No. 3, pp. 223-331
energy and design-for-manufacturing research in an undergraduate research project. In: Proceedings of the 33rd Annual Frontiers in Education Conference. 2003:S1E-10-5.14. Yildiz F, Coogler KL, Pecen RR. An overview: Applied interdisciplinary renewable energy projects. In: Proceedings of the 2012 ASEE Annual Conference & Exposition, San Antonio, Texas, USA. 2012:1-18.15. Zhuo X, Ding J, Yang X, Chen S, Yang J. The experimentation system design and experimental study of the air-conditioning by desiccant type using solar energy. In: Proceedings of the 6th International Conference for Enhanced Building Operations, Shenzhen, China. 2006:1-8.16. U.S. Energy Information Administration. Annual Energy Review 2010. 2011
Optimization: State of the Art: SIAM, 19973 Kodiyalam S, Sobieszczanski-Sobieski J. Multidisciplinary Design Optimization - some formal methods, framework requirements, and application to vehicle design. International Journal of Vehicle Design 2001; 25:3-224 Sobieszczanski-Sobieski J. Multidisciplinary design optimization (MDO) methods: Their synergy with computer technology in the design process. Aeronautical Journal 1999; 103:373-3825 Xiaoyu G, Renaud JE, Penninger CL. Implicit uncertainty propagation for robust collaborative optimization. Transactions of the ASME. Journal of Mechanical Design 2006; 128:1001-10136 Tovar A, Khandelwal K. Topology Optimization for Minimum Compliance using a Control Strategy
assessment of their own learning. The application functions as part of a largerarchitecture we designed to allow a teacher to monitor learning during class and gain evendeeper insights during subsequent offline analysis. A pilot study revealed our architecture wasable to successfully record and support analysis of our students’ self-reported learningassessments. Notably, the architecture serves as a useful tool for spotting trends in studentlearning that, when combined with video of a class, can be a powerful critique.References1 Bloom, Benjamin S., Engelhart, M. D., Furst, Edward J., Hill, Walker H. and Krathwohl, David R. (1956) ‘Taxonomy of educational objectives: Handbook I: Cognitive domain’. New York: David McKay, 19, p. 56.2
., and D. V. Watkins, “Beyond Leadership,” International Journal of Business and Social Science, Vol. 3, No. 4, 2012, pp. 22-30.20. Schindel, W.D., S.N. Peffers, J.H. Hanson, J. Ahmed, and W.A. Kline, “All Innovation is Innovation of Systems: An Integrated 3-D Model of Innovation Competencies,” Presented at American Society for Engineering Education Annual Conference and Exposition, Vancouver, Canada, 2011. Available online at: http://www.google.com/url?sa=t&rct=j&q=&esrc=s&frm=1&source=web&cd=1&ved=0CCkQFjAA&url= http%3A%2F%2Fwww.asee.org%2Fpublic%2Fconferences%2F1%2Fpapers%2F1370%2Fdownload&ei= 88C4UtKlIOKbygH2z4GgAw&usg=AFQjCNF0gIcZcdvgiM1n_hBbCUsxkYq9RQ&bvm=bv.58187178,d. aWc
clearlyimply a need for engineers to be competent in systems thinking and teamwork/communication,to understand the issues of sustainability, and to work effectively on cross-disciplinary problems.A selected set of (mostly non-technical) KSAs identified as important by a survey conducted atthe ASEE-NSF workshop9 and which stakeholder(s) must be responsible to teach them (inpercentages) are shown in Table 1. The numbers within parentheses next to each KSA indicateits priority in the list of 36 KSAs identified through the survey. The sample data presented belowshows the critical role engineering educators have in instilling these KSAs in the futureengineering workforce.While some of the KSAs identified can be integrated into existing courses through